Philippa Kaur

Plant height (cm)Plant height of black cumin as affected by moringa leaf extract applied at various growth stages is reported in Table 1. Both concentrations of moringa leaf extract significantly affected plant height of black cumin. All growth stages also showed statistically significant results. Mean comparison of control vs treatments and water spray vs rest were also found significant for plant height (cm) of black cumin. Whereas, interaction of moringa leaf extract concentrations and growth stages remained non-significant. With increase in interval of spraying moringa leaf extract, plant height enhanced and thus taller plants (68.15 cm) were recorded when moringa leaf extract was sprayed at stage-7 (40 + 80 + 120 days after sowing), followed by (65.15 cm) stage-4 (40 + 80 days after sowing), while lower plants height (47.45 cm) was recorded in stage-3 (120 days after sowing). The use of moringa leaf extract during critical vegetative development phases increased the black cumin crop’s plant height. Similar results were recorded by Abbas et al.14 that moringa leaf extract enhanced plant height and improved fresh and dried weight of wheat root when compared to control. Taller (62.2 cm) plants were recorded in 20% moringa leaf extract sprayed plots followed by (55.8 cm) 10% moringa leaf extract. Spraying moringa leaf extract on a variety of field crops can boost plants and increase vegetative development15.Table 1 Plant height (cm), number of branches plant−1 fixed oil content (% vw−1) and essential oil content (% vw−1) of black cumin as affected by moringa leaf extract applied at various growth stages.Full size tableBranches plant−1
Branches plant−1 of black cumin were significantly influenced by moringa leaf extract concentrations, stage of application as well as their interaction (Table 1). The planned mean comparison of control vs rest and water spray vs rest were also found significant for branches plant−1. The unsprayed against sprayed treatments of moringa leaf extract showed that in unsprayed plots number of branches plant−1 (39) were less than plants sprayed with moringa leaf extract (61.19). Highest number of branches plant−1 (62.19) were observed 20% moringa leaf extract treated plots. These results are in agreement with Mahmood16 who found that foliar application of MLE contains an adequate amount of stimulating substances that promote cell division and enlargement at a faster rate. Zeatin, a growth hormone found in moringa leaf extract, encourages the growth of lateral buds, which leads to an increase in the number of branches. After pounding 100 g of Moringa leaves in 8 L of water, foliar spray of moringa leaf extract enhanced branches plant−1 in okra17. More number of branches plant−1 (70.66) were attained in plots sprayed with moringa leaf extract at growth stage 7 (40 + 80 + 120 days after sowing), followed by growth stage 4 (40 + 80 days after sowing). The effect of the application of MLE at the rate of 20% at 40 days’ interval increased the number of branches and this may be because of the abundant supply of macro and micronutrients and growth hormones. The result of yield parameters revealed that the yield increased as the frequency of moringa leaf extract increased. This is because hormone enhances formation and development of flowers and ripening of fruits. Hormones also enhance growth and yield by altering photosynthetic distributive pattern within the plants. The findings were also in line with that of Manzoor et al.18 who found that an aqueous extract of moringa significantly influence yield and yield components such as number of branches, number of fruits per plant and fruit weight of tomato. The significant interaction of MLE and growth stages is presented in Fig. 1. Applying moringa leaf extract @ 20% at all growth stages enhanced branches plant−1. Maximum branches plant−1 was observed when moringa leaf extract was sprayed @ 20% at growth stage 7 (40 + 80 + 120 days after sowing) whereas, minimum branches plant−1 was recorded in plants sprayed with 10% moringa leaf extract at growth stage-3 (120 days after sowing). Moringa leaf extract (MLE) increased number of branches. Similar results were recorded by Jain et al.19), who reported MLE positively enhanced plant growth attributes of wheat. He also stated that with increasing MLE concentration and application intervals, the growth parameters such as branches plant−1 were increased in arithmetic order. Plant growth regulators are essential for controlling growth and development of plants20. These plant growth regulators increased yield by changing the dry matter distribution pattern or controlling the growth characteristics in crop plants, depending on the dosage and time of application21. In comparison to control, foliar application of moringa leaf extract resulted in a markedly higher branches plant−1. The increased number of branches plant−1 might be due to Zeatin present in moringa leaf extract, which is very effective in delaying the abscission response10.Figure 1Number of branches plant−1 of black cumin as affected by moringa leaf extract applied at various growth stages.Full size imageFixed oil content (% vw−1)Data concerning fixed oil content (% vw−1) in response to moringa leaf extract applied at various growth stages is given in Table 1 and Fig. 2. Statistical analysis of data indicated that foliar application of various concentrations of moringa leaf extract, their stage of application and interaction of concentrations and growth stages had significantly affected fixed oil content (% vw−1) of black cumin crop. The planned mean comparison of control vs rest and water spray vs rest had significant effect on fixed oil content (% vw−1). Highest fixed oil percentage (35.39%) was recorded when moringa leaf extract was sprayed @ 20%, followed by (34.06%) 10% moringa leaf extract, whereas, control (31.48%) showed lowest fixed oil %. Sakr et al.22 indicated that foliar applications of MLE significantly improved the oil percentage and yield plant−1 and feddan of geranium plants. Application of MLE at growth stage-7 (40 + 80 + 120 days after sowing) showed maximum fixed oil content percentage (37.08%) as compared to all other growth stages. Minimum fixed oil percentage was recorded in growth stage-1 (40 days after sowing). Concerning the interaction of moringa leaf extract vs application stage, highest fix oil (37.45%) was observed when moringa leaf extract @ 20% was applied as foliar spray at growth stage-7 (40 + 80 + 120 days after sowing), followed by (36.71%) moringa leaf extract @ 10% applied at growth stage-7. Lowest fixed oil percentage (31.83%) was observed in plants sprayed with 10% moringa leaf extract at stage 1 (40 days after sowing). According to Rady et al.23, biosynthesis of cytokinins promotes the movement of stem reserves to new shoots, resulting in stable plant development, the prevention of premature leaf senescence, and the preservation of more leaf area for photosynthetic action.Figure 2Fixed oil content (%) of black cumin as affected by moringa leaf extract applied at various growth stages.Full size imageEssential oil content (% vw−1)Essential oil content (% vw−1) is a vital oil component of black cumin. Moringa leaf extract concentrations and stage of their application had significant effect on essential oil content of black cumin while the interaction remained non-significant (Table 1). Application of MLE at 20% resulted in higher essential oil yield (0.38%) followed by 10% moringa leaf extract (0.37) sprayed plots. Control plots resulted in lower essential oil (0.33%) content of black cumin. Many research ventures around the world are currently focusing on increasing the biomass yield and volatile oil output of aromatic plants. Moringa leaf extract has been discovered to be an excellent bio-stimulant for enhancing not only crop growth but also yield24,25. According to Aslam et al.26, Plant treated with MLE had major impacts, including an average rise in oil concentrations. Interestingly, MLE treatment not only increased the coriander fruit yield but also improved the fruits volatile oil suggesting that MLE could be a promise plant growth promoter that improved the content of volatile oil in coriander. MLE application also positively affected the volatile oil constituents (Table 2). Increasing the volatile oil in coriander by MLE could be due to the MLE components including amino acids, nutrient elements and phytohoromes that motivate the accumulation of secondary metabolites27. The phytohormones affect the pathway of terpenoids through motivating the responsible physiological and biochemical processes28. Concerning the application stages of moringa leaf extract, higher essential oil content % of black cumin (0.42%) was observed in growth stage-7 (40 + 80 + 120 days after sowing), followed by (0.39%) growth stage-4 (40 + 80 days after sowing), whereas, lower essential oil content % (0.36%) of black cumin was observed in growth stage-1 (40 days after sowing). Plant growth regulators are essential for controlling the amount, type, and direction of plant growth, development, and yield20. These plant growth regulators increased yield by changing the dry matter distribution pattern or controlling the growth characteristics in crop plants, depending on the dosage and time of application21. Exogenous application of MLE resulted in higher yield and quality29.Table 2 Peroxidase value (meq kg−1) and Iodine value (g of I2/100 g) of black cumin as affected by moringa leaf extract applied at various growth stages.Full size tablePeroxidase value (meq kg−1)The response of MLE and stage of MLE application recorded for peroxidase value is stated in Table 2. The data depicted that moringa leaf extract concentrations, stage of application and their interaction had significant (P ≤ 0.05) variation in peroxidase value of black cumin. Similarly, when means were compared, that of control vs treatments and water spray check vs treatments were found significant for peroxidase value (%). Mean value of data indicated that highest peroxidase value (6.32%) was recorded in 20% moringa leaf extract treated plots, followed by (6.03%) 10% moringa leaf extract. While in case of application stages, highest peroxidase value (6.42%) was recorded when moringa leaf extract was applied at stage-7 (40 + 80 + 120 days after sowing), followed by (6.39%) stage-6 (80 + 120 days after sowing). Whereas lowest peroxidase value (5.73%) was recorded in plots treated with moringa leaf extract at stage-3 (120 days after sowing). Interaction of moringa leaf extract concentrations and stage of application in Fig. 3 showed that increasing moringa leaf extract concentration from 10 to 20% applied at growth stage-7 increased peroxidase value of black cumin crop. However, application of moringa leaf extract @ 10% applied at growth stage-3 (120 days after sowing) showed lowest peroxidase value. The phytohormones affect the pathway of terpenoids through motivating the responsible physiological and biochemical processes28. Our results are in agreement with the reports of Ali et al.27 in geranium and Abdel-Rahman and Abdel-Kader30 in fennel who observed that MLE application improves both the volatile oil yield and its components. The fact that MLE application improved black cumin growth and quality characters suorts the study’s hypothesis that MLE is an important plant growth enhancer. In agreement with our results, Rady and Mohamed28 concluded that MLE is considered one of the important plant bio stimulants because it contains antioxidants, phenols, basic nutrients, ascorbates, and phytohormones. Furthermore, foliar application of moringa leaf extract may have a positive effect on endogenous phytohormone concentrations, resulting in improved plant growth and quality10,37.Figure 3Peroxidase value (meq kg−1) of black cumin as affected by moringa leaf extract applied at various growth stages.Full size imageIodine value (g of I2/100 g)Data concerning iodine value of black cumin oil in response to various concentrations of MLE applied at various growth stages is given in Table 2 and Fig. 4. Statistical analysis of data indicated that both the concentrations of moringa leaf extract, stage of application as well as their interaction had significant effect on iodine value of black cumin oil. The planned mean comparison of control vs rest and water spray vs rest treatments had significant effect on iodine value. Highest iodine value (85.3) was recorded with application of moringa leaf extract @ 20% whereas, lowest (78.28) was observed in control. Regarding the stage of application, highest iodine value (87.35) was observed in plots sprayed with moringa leaf extract at stage-7 (40 + 80 + 120 days after sowing), followed by (85.61) plots sprayed with moringa leaf extract at growth stage-6 (80 + 120 days after sowing). Concerning the interaction of MLE concentrations and stage of application of MLE, highest iodine value (6.49) was observed with 20% moringa leaf extract sprayed at stage-7 (40 + 80 + 120 days after sowing) whereas, lowest iodine value was observed in plants sprayed with moringa leaf extract @ 20% applied at stage-3 (120 days after sowing). The use of plant growth regulators is very specific and depends to achieve specific results like for example; enhanced plant growth, betterment in yield and yield related attributes, and to modify the fruit and plant bio-constituents. Several previous studies reveled that MLE are enriched with many phtyo-hormones especially zeatin31. In addition to that MLEs are embedded with many essential amino acids, vitamins (A, B1, B2, B3, C and E), minerals as well as several antioxidants like phenolic32,33. This unique biochemical composition of MLE showed that they can be utilized as bio stimulant which have the potential to promote crop growth, productivity as well as quality which in return depends on its application time34.Figure 4Iodine value (meq kg−1) of black cumin as affected by moringa leaf extract applied at various growth stages.Full size imageTotal free amino acidsThe data presented in Table 2 revealed that moringa leaf extract concentrations and application stages had significantly affected total free amino acid content of black cumin crop during rabi 2019-20 under agro-climatic conditions of Haripur whereas, their interaction remained non-significant. The planned mean comparison of control vs rest and water spray vs rest had significant effect on total free amino acids of black cumin. Highest amino acids (336.3) were observed with the application of moringa leaf extract @ 20%, followed by application of moringa leaf extract @ 10%. Regarding application stages, highest total free amino acids (364.2) were observed with the application of moringa leaf extract at 40 + 80 + 120 days after sowing, followed by (355.9) application of MLE at 40 + 80 days after sowing. Lowest total free amino acids (290.3) were recorded with moringa leaf extract sprayed at 40 days after sowing. Several investigations have demonstrated that MLE can alter both primary and secondary metabolism, resulting in an increase in antioxidant molecule concentrations35,36. The content of phenolic antioxidants, total soluble proteins, and total free amino acids increased in spinach plants treated with synthetic growth regulators and MLE26. MLE can also increase fruit quality metrics in ‘Kinnow’ mandarins, such as soluble solid contents, vitamin C, sugars, total antioxidant, phenolic contents, and superoxide dismutase and catalase enzyme activities, when treated at various growth stages37.Total phenolicPhenolic have acquired much importance because of their properties of disease preventing and health promoting. The effect of moringa leaf extract concentrations, stage of application and their interaction is presented in Table 2. Analysis of variance revealed that moringa leaf extract concentrations and stage of application of moringa leaf extract had significant effect on total phenolic content of black cumin while their interaction remained non-significant. Our results depict that all MLE levels enhanced the total phenolic content of black cumin leaves relative to the control. Highest phenolic content (71.59 mg g−1) was observed with application of moringa leaf extract at the rate of 20%, followed by (68.72 mg g−1) moringa leaf extract application at the rate of 10%. Regarding application stages, highest phenolic content (81.23 mg g−1) was observed with the application of moringa leaf extract at growth stage-7 (40 + 80 + 120 days after sowing), followed by (76.66 mg g−1) stage-6 (80 + 120 days after sowing), whereas, lowest phenolic content (55.25 mg g−1) was observed in crop sprayed with moringa leaf extract at stage-3 (120 days after sowing). In the medicinal, biological, and agricultural areas, phenolic and their derivatives gained scientists attention. Recent studies had focused on their potential as antioxidant-rich natural chemicals38. The increased content of phenolics, flavonoids, and phytohormones in moringa leaves, which may have contributed to the enhanced total phenolic content in black cumin leaves, can be linked to the higher content of phenolics, flavonoids, and phytohormones in MLE treated plants26. Furthermore, the proper concentrations of minerals, vitamins, and -carotene found in moringa leaves may have influenced metabolic processes in a way that increased the internal phenolic content in black cumin leaves, either directly or indirectly39. Therefore, these aspects assist MLE to serve as growth enhancer and natural antioxidant40. Our results supported by the previous report of Nasir et al.37 who revealed that the total phenolic content was enhanced as a result of MLE application at critical stages of plant growth. More

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Driven by the land-to-river and upstream-to-downstream WBIF, biodiversity information across terrestrial and aquatic biomes could be detected in riverine water eDNA6,16, and the monitoring effectiveness of riverine water eDNA relies on the transportation effectiveness of corresponding WBIF6,17,18,19,20. The transportation effectiveness of WBIF mainly relies on the transport capacity, degradation rate, and environmental filtration of WBIF15,21,22,23, which can vary with different seasons and weather conditions26. We hypothesized that the monitoring effectiveness would vary with the seasons and weather conditions. In the present case, the bacterial community richness in riparian soil did not vary with season, whereas the bacterial community composition in riverine water was richest in the autumn, followed by the summer (Figs. 2, 3). The transportation effectiveness of riparian-to-river and upstream-to-downstream WBIF in spring frozen days was significantly lower than in summer rainy days and autumn cloudy days (Tables 1, 2, Supplementary Tables S3, S4). Considering the insufficient read depth on the riverine water samples of summer and autumn groups (Supplementary Fig. S1), the riverine water bacterial community richness and the riparian-to-river transportation effectiveness on summer and autumn were already underestimated. It indicates that the monitoring effectiveness varied with different seasons and weather conditions, and summer and autumn were the optimal seasons, along with rainy days being the optimal weather condition, for using riverine water eDNA to simultaneously monitor the holistic biodiversity information in riverine sites and riparian sites.The biodiversity information detected by water eDNA could originate from living and dead organisms23,26. The detection of biodiversity information that originates from a living organism mainly depends on the dispersal of this living organism11,20. The detection of biodiversity information that originates from a dead organism mainly depends on its transport capacity and degradation rate12,22,29. In summer and autumn, as driven by active organisms, more eDNA was input into the river system. In particular, the surface runoff caused by rain can input more eDNA from terrestrial soil into the river system and can preserve them in soil aggregates30. In the present study, the highest proportion of bacteria in riparian soil was detected in riverine water in summer and autumn, and the rain promoted this phenomenon (Fig. 3 and Table 1, Supplementary Table S3). The proportion of effective upstream-to-downstream WBIF was significantly higher in summer and autumn than in spring, as well as being higher on rainy days than on cloudy days (Table 2). eDNA (originated from dead organisms) degrades over time in a logistic manner (a half-life time)12,22,27,31, which was described in this study as degrading by half-life distance in a lotic system, which integrates the transport capacity and the degradation rate. In the present work, as driven by runoff discharge and flow velocity (Supplementary Table S1), the half-life distance of noneffective WBIF was significantly farther in the summer than in autumn and in spring (Table 2).The biodiversity information monitoring effectiveness of riverine water eDNA, as approximated by the transportation effectiveness of WBIF, was impacted by the eDNA degradation rate in WBIF, and there were taxonomy-specific eDNA degradation rates27, species-specific eDNA degradation rates17, and form-specific eDNA degradation rates28. We hypothesized that the monitoring effectiveness of riverine water eDNA would vary with taxonomic communities. In the present case, the results revealed the detection of a significantly higher monitoring effectiveness of riverine water eDNA (both riparian-to-river and downstream-to-upstream) for bacterial communities than for eukaryotic communities (Tables 3, 4). Considering the insufficient read depth on the bacterial community (16S rRNA gene, Supplementary Fig. S2), the detection capacity on bacterial group was already underestimated. A significantly higher monitoring effectiveness of riverine water eDNA was found for micro-eukaryotic communities (fungi) than for overall eukaryotic communities (including micro- and macro-organisms) (Tables 3, 4). This indicates that the monitoring effectiveness varied with different taxonomic communities, and the effectiveness of monitoring eukaryotic communities was significantly lower than for monitoring bacterial communities; in addition, the effectiveness of monitoring macrobe communities was significantly lower than for monitoring microbe communities.eDNA surveys that are based on metabarcoding can actually acquire information across the taxonomic tree of life5,6,11,32,33. However, eDNA that originates from different taxonomic groups has a different probability of being left in the environment and input into water6,8,9,34. van Bochove et al. inferred that the eDNA contained inside of cells and mitochondria is especially resilient against degradation (i.e., intracellular vs. extracellular effects)28. In the present case, more bacteria than eukaryotes and more microorganisms than macroorganisms (both OTU and species levels) in riparian soil could be detected in riverine water (Table 3). The half-life distance of noneffective WBIF for bacteria (detected by the 16 s RNA gene) was much farther than that for unicellular eukaryotes (detected by the ITS gene, which is mainly unicellular), than that for multicellular eukaryotes (as detected by the CO1 gene, which is mainly multicellular) (Table 4). We inferred that the eDNA contained inside of bacterial cells was more resilient against degradation than that contained inside of unicellular eukaryotic cells (i.e., prokaryotic cells vs. eukaryotic cells), as well as compared to the eDNA contained inside of multicellular eukaryotic cells or extracellular mitochondria (i.e., unicellular eukaryotic cells vs. multicellular eukaryotic cells or extracellular mitochondria).In previous studies, the effectiveness of using water eDNA to monitor terrestrial organisms was indicated by the detection probability8,9,34, and the effectiveness of using downstream water eDNA to monitor upstream organisms was indicated by the detectable distance7,12,17,19,20,35. In this study, we approximated the biodiversity information monitoring effectiveness by the WBIF transportation effectiveness and proposed its assessment framework, in which we described the riparian-to-river monitoring effectiveness with the proportion of biodiversity information in riparian soil that was detected by using riverine water eDNA samples. Additionally, we described the downstream-to-upstream monitoring effectiveness with the proportion of biodiversity information in upstream site water eDNA samples that was detected by 1-km downstream site water eDNA samples, and the runoff distance of that 50% of dead bioinformation (i.e., the bioinformation labeling the biological material that lacked life activity and fertility) could be monitored. These indicators provided new usable assessment tools for designing monitoring projects and for evaluating monitoring results.In the optimal monitoring season and weather condition (a summer rainy day) in the Shaliu river basin on the Qinghai–Tibet Plateau, by using riverine water eDNA, we were able to monitor as much as 87.95% of bacterial species, 76.18% of fungal species, and 53.52% of eukaryotic species from riparian soil, along with as much as 98.69% of bacterial species, 95.71% of fungal species, and 92.41% of eukaryotic species from 1 km upstream (Table 4). The half-life distance of the noneffective WBIF was respectively 17.82 km, 5.96 km, and 5.02 km for bacteria, fungi, and metazoans at the species level (Table 4). When considering the fact that the monitoring effectiveness of eDNA can not only vary with season, weather, and taxonomic communities, but can also vary with rivers and watersheds with different environmental conditions12,17,19,23, more studies on the monitoring effectiveness for each taxonomic community in other watersheds with different environmental conditions are needed.eDNA metabarcoding surveys are relatively cheaper, more efficient, and more accurate than traditional surveys in aquatic systems10,13, although this is certainly not true in all circumstances36. Sales et al. show that the detection probability of using riverine water eDNA to monitor the semi-aquatic and terrestrial mammals in natural lotic ecosystems in the UK was 40–67%, which provided comparable results to conventional survey methods per unit of survey effort for three species (water vole, field vole and red deer); in other words, the results from 3 to 6 water replicates would be equivalent to the results from 3 to 5 latrine surveys and 5–30 weeks of single camera deployment9. In the current case, the riverine water eDNA samples detected 53.52% of eukaryotic species from riparian soil samples. As the bioinformation in WBIF includes the biodiversity information of all taxonomic communities, the information of all taxonomic communities could be monitored by using riverine water eDNA, although variability in monitoring effectiveness exists among different taxonomic communities. We anticipate that, in future biodiversity research, conservation, and management, we will be able to efficiently monitor and assess the aquatic and terrestrial biodiversity by simply using riverine water eDNA samples.In summary, to test the idea of using riverine water eDNA to simultaneously monitor aquatic and terrestrial biodiversity, we proposed a monitoring effectiveness assessment framework, in which the land-to-river monitoring effectiveness was indicated by detection probability, and the upstream-to-downstream monitoring effectiveness was described by the detection probability per kilometer runoff distance and by the half-life distance of dead bioinformation. In our case study, in the Shaliu River watershed on the Qinghai-Tibet Plateau, and on summer rainy days, 43–76% of species information in riparian sites could be detected in adjacent riverine water eDNA samples, 92–99% of species information from upstream sites could be detected in a 1-km downstream eDNA sample, and the half-life distances of dead bioinformation for bacteria was approximately 13–19 km and was approximately 4–6 km for eukaryotes. The indicators in the assessment framework that describe the monitoring effectiveness provide usable assessment tools for designing monitoring projects and for evaluating monitoring results. In future ecological research, biodiversity conservation, and ecosystem management, riverine water eDNA may be a general diagnostic procedure for routine watershed biodiversity monitoring and assessment. More

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Dataset of beneficial plantsI collated a species-level dataset of plant benefits (presence/absence data) starting from the information gathered by Kleunen et al.32. These authors extracted data from the WEP database (National Plant Germplasm System GRIN-GLOBAL; https://npgsweb.ars-grin.gov/gringlobal/taxon/taxonomysearcheco.aspx, Accessed 7 Jan 2016), which is based on the book by Wiersema and León20. Their dataset included 84 categories and subcategories of plant benefits pertaining human and animal nutrition, materials, fuels, medicine, useful poisons, social and environmental benefits. Subcategories of benefits, which often included very few records, were merged here into 25 standard and major categories following the guidelines in the Economic Botany Data Collection Standard33 as in Molina-Venegas et al.13, namely ornamental plants, soil improvers, hedging/shelter, human food, human-food additives, vertebrate food, invertebrate food, fuelwood, charcoal, other biofuels, timber, cane/stems, fibres, tannins/dyestuffs, beads, gums/resins, lipids, waxes, essential oils/scents, latex/rubber, medicines, invertebrate poison, vertebrate poison, smoking materials/drugs and symbolic/inspirational plants (Fig. 1). A few records (n = 93) that could not be assigned to any of the above categories were disregarded, and so was the category ‘gene source’ because unlike other benefits, any species is intrinsically a potential gene donor and hence there is not a clear link between the benefit and species features. Note that this is not to say that preserving genetic diversity, which indeed is the underlying message of this research, is a meaningless goal. Infraspecific taxa were collapsed at the species level, and the very few fern taxa in the original database32 were excluded. In total, I gathered 15,834 plant-benefit records sorted in a matrix of 25 types of benefits and 9521 species of seed plants. Most species (83.74%) provided only one or two benefits representing 62.83% of the records in the dataset, and the maximum number of benefits per species was 10 (only three species). Although the WEP database is the largest species-level database on plant benefits32, it does not claim to be comprehensive20. Yet, the size of the dataset I gathered here represented 76.19% of the total seed-plant genus-level records collated for the same types of benefits in a more comprehensive survey by Molina-Venegas et al.13 that based on Mabberley’s Plant-book34. Moreover, the total number of records per category (at the genus-level) strongly correlated between the datasets (Pearson r = 0.94, p  More